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From |
Austin Nichols <austinnichols@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: RE: Question on survey data analysis |

Date |
Tue, 2 Mar 2010 10:41:54 -0500 |

Michelle [Z.Ou@warwick.ac.uk]: As I understand it, the 7-option question "Why don't you join any loyalty schemes?" is to be used as a set of dummy variable predictors on the right hand side, where the outcome variable is either not_want_to_join_loyalty_scheme or aware_of_one_of_ten_different_retailers_w_loyalty_schemes (so, probably a logit or probit regression with other explanatory variables included). If you have Stata 11, and the answers are mutually exclusive, you need not define dummy variables for a categorical variable; see http://www.stata.com/help.cgi?fvvarlist (but if you have an earlier version of Stata see http://www.stata.com/help.cgi?tabulate+oneway and the generate option). It sounds like people can check off as many or as few answers as they like, though, so each of the seven options should be a separate dummy variable, i.e. you do not have a categorical variable measuring which one choice was made among the seven. If you have survey data, you should -svyset- to identify clusters, and probably weights. Even if the original sample was a simple random sample (SRS), you may want to deal with nonresponse by weighting, or poststratify to match the underlying population's characteristics. If you describe your survey design in more detail, you will probably get better answers on that topic. On Tue, Mar 2, 2010 at 7:57 AM, Nick Cox <n.j.cox@durham.ac.uk> wrote: > Working backwards, your last question appears to be whether you should > use the -svy- commands. ... > http://www.stata.com/support/faqs/data/multresp.html > Michelle [Z.Ou@warwick.ac.uk] > > I designed a survey about loyalty schemes > (e.g. tesco clubcard that sort of programmes) for my economics research > project, but not sure how to compute multiple choice questions in the > questionnaire. > > One of my questions was: 'Why don't you join any loyalty schemes?' and > my list of answers include: a) poor customer service, b) unachievable > rewards, c) unrealistic points, d) too much marketing communications, e) > redeeming schemes too complicated, f) choice of rewards available and g) > others, i.e. 7 options in total. > > Respondents were asked to tick all that apply. I want to see which are > the > most deterring factors of the list that make these students not want to > join loyalty schemes. Could someone give me any hints? Do I have to > create > a new dummy variable for each of the seven alternatives? > > A similar question asked which, if any, respondents are aware of out of > a > list of ten different stores/retailers who have loyalty schemes. Again, > do > I have to treat each option as a independent dummy? > > Also do I have to declare data type as survey data to carry out any > further analysis? Or is it alright for me to do simple regression > analysis > without letting stata know it's survey data I'm working with? Does it > affect my results? * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: Question on survey data analysis***From:*Z.Ou@warwick.ac.uk

**st: RE: Question on survey data analysis***From:*"Nick Cox" <n.j.cox@durham.ac.uk>

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